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Unsupervised Learning of Graph Hierarchical Abstractions with
  Differentiable Coarsening and Optimal Transport

Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport

24 December 2019
Tengfei Ma
Jie Chen
ArXivPDFHTML

Papers citing "Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport"

5 / 5 papers shown
Title
A Unified Framework for Optimization-Based Graph Coarsening
A Unified Framework for Optimization-Based Graph Coarsening
Manoj Kumar
Anurag Sharma
Surinder Kumar
18
10
0
02 Oct 2022
Accelerating Training and Inference of Graph Neural Networks with Fast
  Sampling and Pipelining
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
Tim Kaler
Nickolas Stathas
Anne Ouyang
A. Iliopoulos
Tao B. Schardl
C. E. Leiserson
Jie Chen
GNN
70
52
0
16 Oct 2021
Blockchain Phishing Scam Detection via Multi-channel Graph
  Classification
Blockchain Phishing Scam Detection via Multi-channel Graph Classification
Dunjie Zhang
Jinyin Chen
28
28
0
19 Aug 2021
Graph coarsening: From scientific computing to machine learning
Graph coarsening: From scientific computing to machine learning
Jie Chen
Y. Saad
Zecheng Zhang
20
39
0
22 Jun 2021
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
172
1,775
0
02 Mar 2017
1